The key to few-shot segmentation is how to effectively utilize provided support samples for a query image. While conventional methods [1]}, [2]}, [3]}, [4]}, [5]} attempted to utilize global- or part-level prototypes extracted from support features, recent methods [6]}, [7]}, [8]}, [9]}, [10]}, [3]} attempted to leverage pixel-wise relationships between query and support. One of the latest work, HSNet [8]}, attempts to aggregate the matching scores with 4D convolutions, but it lacks an ability to consider interactions among the matching scores due to the inherent nature of convolutions.
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